While implementing speech signal coding systems for medium bit-rate transmission (e.g. 16kbit/s), the main problem to resolve is that of the quality of representation of the signal by exploiting the entire body of knowledge of production and perception speech-signal models, maximizing reproduction quality versus the desired bit rate.
From that point of view the systems which analyze total-band speech signal do not optimally exploit its characteristics, since the spectrum is non-uniform, i.e. its characteristics are considerably different as a function of the frequency region considered.
Then, by previously splitting the speech signal spectrum into independently-analyzed subbands, a piece-wise approximation is obtained; i.e. a more accurate shaping of the full spectrum, rendering the coding method more flexible and efficient.
A speech-signal coding system by a band splitting is described in the paper by R. S. Cheung, S. Y. Kwon: "The design of a 16kbit/s split-band adaptive predictive coder for noisy channels", Proceedings of International Conference on Acoustics, Speech and Signal Processing, Atlanta, 1981, pp. 631-635.
According to this method the speech signal is split into two subbands.
Each subband is quantized by using a method of adaptive linear prediction and dynamic bit allocation which also calculates additional parameters such as spectral parameters which are scalarly quantized. The sampling frequency used is 6.4 kHz.
The splitting into two subbands is insufficient to approximate the signal spectrum to the degree desired. More particularly, subband quantizer determinations are hardly accurate and flexible, and a dynamic bit allocation over two subbands renders it difficult to follow with sufficient accuracy energy variations inside the spectrum.
Besides, the scalar quantization of spectral parameters entails the transmission of a considerable number of bits devoted to additional information, with consequent reduction in the availability of bits devoted to subband quantization; it furthermore reduces acoustic background noise immunity, since spectral parameters are calculated on the input-signal spectrum which can be noise-affected. The noise alters also quantized parameters. In addition, the use of predictive algorithms for higher speech-band frequencies is of limited efficiency owing to the scanty correlation existing between said subband samples. Finally, the used sampling frequency entails the additional insertion of apparatus to allow interfacing with standard transmission devices, e.g. on a telephone network operating at 8 kHz frequency.